Single cell sequencing analysis of Foxp3 - IL-10 producing CD4 positive T cells

In summary, the population of Foxp3^- IL-10 producing CD4 positive T cells in the kidneys displayed a low expression of IL-10, CD49b, LAG3, TIM3 and TIGIT when only glomerulonephritis was induced in the mice. The additional treatment of nephritic mice with an anti-CD3 specific antibody, which is known to induce tolerance [105, 148, 149], increased the frequencies of IL-10 producing cells infiltrating the kidneys. However, within this Foxp3^- IL-10producing CD4 positive T-cell population, also upon CD3-specific antibody treatment only a small fraction of around 8 % of the cells expressed CD49b and LAG3, the markers which have previously been reported to identify suppressive cells in the gut [8]. Therefore, these data suggest that the majority of Foxp3^- IL-10 producing T cells in the inflamed kidney might not have a regulatory function.

3.2.2 Single cell sequencing analysis of Foxp3^- IL-10 producing CD4

Figure 11: Experimental setup and sorting strategy for RNA single cell sequencing

A) Experimental setup Foxp3^mRFP IL-10^eGFP IL-17A^Katushka IL-17A^CRE Rosa26^YFP mice were injected with nephrotoxic nephritis serum. Ten days after injection, kidneys of 25 male mice were pooled. B) 40.000 Foxp3^- IL-10 producing CD4 positive T cells were sorted accordingly to the gating strategy.

First, similarities between IL-10 producing CD4 positive T cells derived from different organs were closely examined. Previously, a suppressive cluster was identified in small intestine and spleen derived IL-10 producing CD4 positive T cells [8]. Furthermore, we wondered whether a tSNE cell clustering would result in an overlap between similar cells from the different organs. Therefore, tSNE analysis of all cells from three different organs was performed. For this tSNE analysis of the spleen and the small intestine, the raw single cell sequencing data, generated by Brockmann et al., were used [8]. This clustering revealed three big clusters, whereas each cluster mainly represented one organ (Figure 12A). Only a small subpopulation of the small intestine sample clustered apart (Figure 12A).

Another small subset of splenic IL-10 producing CD4 positive T cells clustered closer to the kidney cluster (Figure 12A). Nevertheless, the strongest differences on which clustering was based were actually determined by the organs of which the cells originally derived.

Next, when each organ was analyzed individually, analysis showed distinct sub-clustering in all three organs (Figure 12B + C). The kidney showed 5 different clusters (C0-C4) (Figure 12B), same as the small intestine, that separated in 5

clusters (C0-C4) (Figure 12C). The highest number of 7 clusters (C0-C6) was found in IL-10 producing CD4 positive T cells isolated from the spleen (Figure 12C).

Next, via Spearman correlation, every cluster of each organ was cross-compared to the others.

Previously, one cluster of small intestine and spleen were identified to be highly suppressive. These cells are in the presented analysis in splenic cluster C4 and the cluster C0 from the intestine, although the majority of cells in the small intestine had suppressive function at different levels [8]. The cross-comparison between the clusters from the kidney and the small intestine revealed no similarities (Figure 12D white to blue colors). However, some clusters from the kidneys correlated with some of the spleen (Figure 12D pink to red colors). There was a higher similarity between kidney cluster 2 and spleen clusters 5 and 1 (Figure 12D). Furthermore, kidney cluster 4 showed high similarities with spleen cluster 3. Lastly, kidney cluster 1 displayed milder similarities with spleen cluster 2 (Figure 12D).

Nonetheless, spleen cluster 4 and small intestine cluster 0, which were previously described to be the highly suppressive clusters didn’t show similarities with any of the clusters found in the kidney. As expected, the highly suppressive spleen cluster 4 displayed high similarities with all small intestine clusters except cluster 3. Thus, it seems that the heterogeneous Foxp3^- IL-10 producing CD4 positive T-cell population from the inflamed kidney is, on a transcriptional level, distinctly different from the ones observed in the intestine and spleen. However, this does not exclude the possibility that some of the clusters in the kidney might have a transcriptional signature of regulatory TR1 cells, which might be still overall distinct from the once in spleen and intestine.

Therefore, we next aimed to assess, whether Foxp3^- IL-10 producing CD4 positive T cells would express a regulatory transcriptional signature of TR1 cells.

Previously, bulk sequencing was performed with IL-10positive CD49b⁺ LAG3⁺,

IL-10 positive but not CD49b⁺ LAG3⁺ and IL-10negative, CD49b^- LAG3^- CD4 positive T cells from the spleens of anti-CD3 specific antibody treated mice. This analysis was used to identify the transcriptional signature profile of TR1 cells [8].

The score included the expression of cytokines, transcription factors, receptors and other markers such as integrins and chemokine receptors [8]. To test whether the kidneys contains Foxp3^- IL-10 producing CD4 positive T cells positive for this signature, the signature was overlaid on single cell data from the kidney. This result was compared with an overlay of the TR1 transcriptional signature on top of splenic and small intestine derived IL-10 producing CD4 positive T cells.

Indeed, we had previously shown that cells within this profile are mainly in small intestine cluster 0 (30 %) and spleen cluster 4 (8 %) [8]. This observation could be confirmed also with the new clustering (Figure 12E).

Interestingly, around 30-40 % of the kidney derived Foxp3^- IL-10 producing CD4 positive T cells from nephritic mice displayed a transcriptional signature similar to the one of a TR1 cell (Figure 12E). Most of the cells in clusters 3 and 4 showed intermediate to high expression for the previously defined TR1 signature (Figure 12E light dots). Cluster 0 showed a very heterogeneous cluster regarding the TR1 signature. Nonetheless, a small portion of Cluster 0 displayed also intermediate to high expression of the TR1 transcriptional signature. Cluster 1 and 2 showed a low TR1 transcriptional signature expression (Figure 12E dark dots).

Taken together, the population of Foxp3^- IL-10 producing CD4 positive T cells from different organs did not show similarities between the kidney compared to the small intestine and spleen. Nonetheless, 30 % of Foxp3^- IL-10 producing CD4 positive T cells in the kidney displayed the transcriptional signature of a TR1 cell.

Figure 12: Score of cells with transcriptional TR1 gene signature

A) Clustering of IL-10 producing CD4 positive T cells from small intestine and spleen of anti-CD3 specific antibody treated mice together with Foxp3^- IL-10 producing CD4 positive T cells from nephritic kidneys. B) + C) clustering of in A mentioned IL-10 producing single cells D) Correlation between clusters formed in B) +C). E) Expression levels of cells positive for “TR1”-gene signature based on previous Bulk RNA-sequencing data

tSNE2

tSNE1

0 0,2 0,4 0,6 0,8 1,0

0 0,2 0,4 0,6 0,8

Kidney (NTN) Spleen (aCD3) 1,0

0 0,2 0,4 0,6 0,8 Small intestine (aCD3)1,0

tSNE2

tSNE1

Kidney (NTN) Small intestine (aCD3) Spleen (aCD3)

2 4 0 3 1 3 0 1 5 2 6 0 4 1 2 3 4 -1.00 -0.75 -0.50 -0.25 0.00 0.25 0.50 0.75 1.00 4 3 2 1 4 0 6 2 5 1 0 3 1 3 0 4 2

Spleen (aCD3) Sma

ll intestine (aCD3)

Spleen (aCD3)

Kidney (NTN)

Kidney (NTN)

Spleen (aCD3)

Small intestine (aCD3)

Spleen (aCD3) A)

C)

C 3 C 2 C 0

tSNE2 C 4 tSNE1

30,12%

19,03%

12,22%

25,57%

13,07% C 1

tSNE2

tSNE1

Small intestine (aCD3)

IL-10pos Spleen (aCD3)

IL-10pos Kidney (NTN)

Foxp3neg IL-10pos B)

D)

E)

C 3 C 2 C 0

C 4 C 1

tSNE2

tSNE1

C 3 C 2 C 0

C 4 C 1

C 6

35,24% C 5

22,85%

15,09%14,54%

12,25%

25,99%

18,58%15,29%

14,26%

10,83%

9,12%

5,89%

Next, we wanted to analyze in more detailed which of the clusters expressed genes associated with regulatory or effector function respectively. Therefore, expression levels of single genes in the different clusters of kidney-derived Foxp3^- IL-10 producing CD4 positive T cells were deciphered. IL-10 cytokine expression, as well as expression levels of surface molecules indicating a suppressive profile were first analyzed. Co-inhibitory receptors such as LAG3, TIM3, TIGIT and PD-1 as well as integrin CD49b, or the chemokine receptor CCR5 are described to be expressed on highly suppressive TR1 cells [8, 97, 112].

Interestingly, as for IL-10 expression, cluster 0, 3 and cluster 4 showed a high, and cluster 1 and 2 displayed low IL-10 gene expression (Figure 13B). The expression of Itga2, the gene encoding for the integrin CD49b was low in all cells (Figure 13B). LAG3, Pdcd1, CCR5 and Ctla4 showed similar expression patterns as IL-10. The highest expression was detected in cluster 0, 3 and cluster 4 (Figure 13B. The lowest expression was seen in cluster 1 and 2 (Figure 13B). Havcr2, the gene encoding for TIM3 was mainly expressed in cluster 0 and 4. However, Tigit showed an overall low expression in all clusters (Figure 13B).

Figure 13: Clustering and gene expression levels of Foxp3^- IL-10 producing CD4 positive single cells

A) tSNE analysis of single cell clustering of 4592 Foxp3^- IL-10 positivecells isolated from the kidneys of nephritic mice B) Expression levels of indicated genes in tSNE-analysis

In the next part of the analysis, effector cytokines and related transcription factors were analyzed. Cluster C0 and C3 showed the highest expression of the transcription factor IRF8 (Figure 14). Maf, the gene encoding for c-Maf was highly expressed within all four clusters. C-Maf is known for its important role during IL-27 induced TR1 differentiation [98]. Prdm1, the gene encoding for Blimp-1 displayed overall low, but homogenous expression in all clusters (Figure 14).

Blimp-1 was described to be important during effector T helper-cell conversion upregulating IL-10 [38]. A small fraction within cluster 1 and 2 showed expression of the TH17 specific signature cytokine Il17a and Rorc, the gene encoding for the corresponding transcription factor ROR-ɣt (Figure 14). Next, gene expression levels of Ifng, the signature cytokine of TH1 cells and Tbx21 (Tbet), the transcription factor for TH1 cells were evaluated. Ifng expression was

C 3 C 2 C 0

C 4

tSNE2

tSNE1 Itga2

00,5 1,0 1,5 2,0 2,5

Lag3

01 2 3 4 5

Tigit

00,5 1,0 1,5 2,02,5

tSNE2

tSNE1

Ctla4

01 2 3 4

Havcr2

00,5 1,0 1,52,0 2,53,0

Pdcd1

0 1 2 3 4

Il10

tSNE2

tSNE1

01 2 3 4 5

tSNE2

tSNE1 30,12%

19,03%

12,22%

25,57%

13,07%

0 1 2 3

Ccr5 C 1 A)

B)

predominantly expressed in cluster 0 and 3 (Figure 14). The expression pattern for Tbx21 was homogeneusly expressed at low levels in all five clusters (Figure 14). Lastly, TH2 related cytokines were investigated. Surprisingly, exclusively cluster C3 showed high expression of Il4 (Figure 14). Il13 was not expressed in any of the clusters (Figure 14). Furthermore, the TH2 related transcription factor Gata3 showed low gene expression in all clusters except cluster 0 (Figure 14).

Figure 14: Gene expression levels of Foxp3^- IL-10producing CD4 positive single cells

Gene expression levels of indicated genes in tSNE-analysis

In conclusion, cluster 0 in the kidney revealed to be the cluster with the highest expression of transcripts, which are typical expressed by a suppressive TR1 cell population. With the lowest IL-10 gene expression, cluster 1 furthermore displayed genes like Il17a, Rorc, Ifng, Tbx21 or Gata3, associated with effector like phenotype. In addition, it showed low expression of the suppressive profile defined by Itga2, Lag3, Havcr2, Tigit, Pdcd1, Ccr5 and Ctla4. Taken together, the analysis of Foxp3^- IL-10positive CD4positive single T cells from the kidneys revealed a heterogeneous cell population. Nonetheless, the genes encoding for the transcriptional TR1 profile were expressed in about 30-40 % of the cells,

tSNE2

tSNE1

tSNE2

tSNE1

tSNE2

tSNE1

01 2 3 4

Irf8

0 1 2 3 4

Maf

Tbx21

0,00,5 1,0 1,52,0 2,53,0

Ifng

01 2 3 4 5

Il4

0 1 2 3 4

Prdm1

0 1 2 3 4

Il17a

0,00,5 1,01,5 2,02,5

0 1 2 3 4

Il13

Rorc

Gata3

0,0 0,5 1,0 1,5 2,0

0 1 2 3

indicating that these cells, despite the low protein expression of CD49b and LAG3, might be regulatory.

3.2.3 In vivo generated Foxp3^- IL-10 producing CD4 positive T cells from

Im Dokument Analysis of TH17-cell plasticity into regulatory fates during crescentic glomerulonephritis in a mouse model (Seite 77-85)